Uninterrupted playback of video streams using lower quality cached files

ABSTRACT

Disclosed are various embodiments for facilitating uninterrupted playback of video streams using lower quality cached files. A video file corresponding to an entirety of a video content feature encoded at a first quality is obtained. A video stream corresponding to the video content feature encoded at a second quality higher than the first quality is then obtained. The video stream is rendered for playback on a display. In response to detecting an unavailability of the video stream at a particular time in the video content feature, the video file is rendered for playback on the display in place of the video stream and commences at the particular time in the video content feature.

BACKGROUND

The advent of widely available, high-speed broadband Internetconnections has also brought about video streaming services. Suchservices, though the use of advanced codecs, are able to offer streamingof high definition (HD) and standard definition (SD) video at bitratesthat are accessible via cable modem or digital subscriber line (DSL)bandwidths at home. HD video may, for example, offer up to 1080 lines ofresolution, interlaced or progressive scan. Availability of video havingeven higher quality is now on the horizon, with displays beginning tosupport 4 k and/or 8 k ultra high definition (UHD) video. Higherbandwidth Internet connections using fiber-to-the-home and/or othertechnologies may be required to stream UHD video.

BRIEF DESCRIPTION OF THE DRAWINGS

Many aspects of the present disclosure can be better understood withreference to the following drawings. The components in the drawings arenot necessarily to scale, with emphasis instead being placed uponclearly illustrating the principles of the disclosure. Moreover, in thedrawings, like reference numerals designate corresponding partsthroughout the several views.

FIG. 1A is a drawing presenting one example of operation of a networkedenvironment according to various embodiments of the present disclosure.

FIG. 1B is a drawing presenting a detailed view of the networkedenvironment of FIG. 1A according to various embodiments of the presentdisclosure.

FIG. 1C is a drawing presenting a view of a networked environment thatfacilitates local cached file exchange according to various embodimentsof the present disclosure.

FIG. 2 is a flowchart illustrating one example of functionalityimplemented as portions of a caching system executed in a client in thenetworked environment of FIG. 1B according to various embodiments of thepresent disclosure.

FIG. 3 is a flowchart illustrating one example of functionalityimplemented as portions of a content access application executed in aclient in the networked environment of FIG. 1B according to variousembodiments of the present disclosure.

FIG. 4 is a flowchart illustrating one example of functionalityimplemented as portions of a content server executed in a computingenvironment in the networked environment of FIG. 1B according to variousembodiments of the present disclosure.

FIG. 5 is a schematic block diagram that provides one exampleillustration of a computing environment employed in the networkedenvironment of FIGS. 1A-1C according to various embodiments of thepresent disclosure.

DETAILED DESCRIPTION

The present disclosure relates to providing uninterrupted playback ofhigh-quality video streams via caching of video files having relativelylower quality. While home-based televisions, set-top boxes andperipherals, desktop computers, and so on may have access to aconsistent, high-bandwidth Internet connection, mobile devices often donot have such a luxury. Mobile devices, such as smartphones, tablets,and laptops, may at times be connected to high-speed wireless local areanetwork (LAN) connections such as WI-FI. At other times, connectivitymay be via a third-generation (3G) or fourth-generation (4G) cellularnetwork, which may or may not be as fast as a wireless LAN. Further,connectivity may be constrained in some areas to 2G speeds, or Internetconnectivity may simply be absent. Network congestion and/or bandwidththrottling may impact wireless LAN or cellular data connections. In somecases, bandwidth may be constrained due to a chosen data plan. Insummary, the network connectivity available to a mobile device may be ofvarying data speeds.

Users frequently are interested in streaming video content such asmovies and television programs to their mobile devices. However, asdiscussed above, the network connectivity to a mobile device may changeover time. While a mobile device may have sufficient networkconnectivity to stream a high-quality video at one location, streamingmay be impossible at another location. Sometimes the change in networkconnectivity may be relatively brief (e.g., due to a small cellular deadspot). If a user enters a dead spot while streaming video content via amobile device, the playback may be interrupted.

Various embodiments of the present disclosure facilitate theuninterrupted playback of video streams through the use of low-qualityvideo files. A low-quality video file for a video content feature may bedownloaded to a mobile device, either before or after the user indicatesan interest in the video content feature. The low-quality video file maybe one or more orders of magnitude smaller in data size as compared tothe data size of the high-quality video stream. The smaller data sizeboth allows for storage upon a mobile device with constrained datastorage resources and allows for a relatively fast download. When ahigh-quality video stream is interrupted, playback may instantaneouslyshift to the cached lower-quality version, thereby avoiding a disruptionof the viewing experience.

Various techniques may be employed in determining which video contentfeatures should be predictively cached. Several approaches to predictivecaching are described in U.S. patent application Ser. No. 13/592,752entitled “PREDICTIVE CACHING FOR CONTENT” and filed on Aug. 23, 2012,and U.S. patent application Ser. No. 14/274,121 entitled “CLIENT-SIDEPREDICTIVE CACHING FOR CONTENT” and filed on May 9, 2014, which areincorporated herein by reference in their entirety.

With reference to FIG. 1A, shown is one example of operation for anetworked environment 100 a according to various embodiments. Thenetworked environment 100 a includes a computing environment 103 in datacommunication with one or more clients 106 via a network 109. The client106 is rendering a user interface 112 corresponding to a video playerthat is playing a movie titled “World of the Gorillas.” The userinterface 112 informs the user that network connectivity to the client106 has been interrupted. In spite of the network connectivityinterruption, playback of the movie continues nonetheless based upon acached version of the movie that is locally available to the client 106.The movie may be cached via predictive caching.

The client 106 includes a cache 118 in memory that stores a plurality ofvideo files 121 a . . . 121N corresponding to each predictively cachedvideo content feature. Through predictive caching, the client 106 isconfigured to obtain the video files 121 from the computing environment103 over the network 109 before the user at the client 106 requests useor playback of the content item. Further, the client 106 may initializevarious software and/or hardware components based at least in part onthe video files 121 in order to provide a seamless experience when theclient 106 switches playback to the video files 121.

After the user requests to play a video content feature, the client 106may then obtain a video stream 130 over the network 109 from thecomputing environment 103. The video stream 130 may correspond to a muchhigher quality video as compared to the video files 121, and the videostream 130 may have a much higher bitrate as compared to the video files121. The difference may be an order of magnitude in comparison or evengreater. When the high-quality video stream 130 becomes unavailable, theclient 106 may seamlessly continue playback via a correspondinglow-quality video file 121. In the following discussion, a generaldescription of the system and its components is provided, followed by adiscussion of the operation of the same.

Turning now to FIG. 1B, shown is a detailed view of the networkedenvironment 100 a according to various embodiments. The networkedenvironment 100 a includes the computing environment 103 in datacommunication with one or more clients 106 via the network 109. Thenetwork 109 includes, for example, the Internet, intranets, extranets,wide area networks (WANs), local area networks (LANs), wired networks,wireless networks, cable networks, satellite networks, or other suitablenetworks, etc., or any combination of two or more such networks.

The computing environment 103 may comprise, for example, a servercomputer or any other system providing computing capability.Alternatively, the computing environment 103 may employ a plurality ofcomputing devices that are arranged, for example, in one or more serverbanks or computer banks or other arrangements. Such computing devicesmay be located in a single installation or may be distributed among manydifferent geographical locations. For example, the computing environment103 may include a plurality of computing devices that together maycomprise a hosted computing resource, a grid computing resource, acontent delivery network, and/or any other distributed computingarrangement. In some cases, the computing environment 103 may correspondto an elastic computing resource where the allotted capacity ofprocessing, network, storage, or other computing-related resources mayvary over time.

Various applications and/or other functionality may be executed in thecomputing environment 103 according to various embodiments. Also,various data is stored in a data store 133 that is accessible to thecomputing environment 103. The data store 133 may be representative of aplurality of data stores 133 as can be appreciated. The data stored inthe data store 133, for example, is associated with the operation of thevarious applications and/or functional entities described below.

The components executed in the computing environment 103, for example,include a prediction engine 136, a content server 139, and otherapplications, services, processes, systems, engines, or functionalitynot discussed in detail herein. The prediction engine 136 is executed togenerate a list of content that a user is predicted to use. To this end,the prediction engine 136 may analyze various behavioral data collectedregarding the user along with other data. The list of contentcorresponds to content that the user is likely to playback or consume.The list may include relative priorities for the content correspondingto a relative strength of prediction. The list may be sent to the client106 over the network 109 as prediction data 142.

In one embodiment, the prediction engine 136 may be configured toreceive various caching metrics 143 reported by the clients 106. Thecaching metrics 143 may indicate a proportion of playback occurrencesfor which a video file 121 was cached and used. In some cases, the cachemetrics 143 may include additional metadata that indicates whyparticular content items were selected to be cached, e.g., which cachesegment cached the particular content item. The sizes of the cachesegments may also be reported, as well as how long it takes to cachespecific content items. The caching metrics 143 may be employed asfeedback to the prediction engine 136 in order to improve futurepredictions according to machine learning techniques.

The content server 139 is executed to serve up video content featuresand associated data to users of clients 106. To this end, the contentserver 139 is configured to send content data 145 to the client 106 viathe network 109. The content data 145 may include both video streams 130and video files 121. In addition, the content server 139 may generateand send user interface data to the client 106 to facilitate userbrowsing, searching, and/or selection of content. Such user interfacedata may correspond to web page data, mobile application data, and/orother forms of user. Such user interface data may include hypertextmarkup language (HTML), extensible markup language (XML), cascadingstyle sheets (CSS), and/or other data. In one embodiment, the contentserver 139 may send directives to the client 106 that instruct theclient 106 to predictively cache preselected video files 121.

The data stored in the data store 133 includes, for example, useraccount data 148, promotion data 149, popularity data 150, a contentlibrary 151, content similarity data 152, and potentially other data.The content library 151 includes data relating to content items that aremade available by the content server 139 for playback, download,viewing, lease, purchase, etc. Such content items may include, forexample, movies, television shows, music, music videos, video clips,audio clips, applications such as mobile applications, and so on. Thecontent library 151 may include content portions 153, metadata such asmanifests 155 and decryption keys 157, content availabilities 158,and/or other data.

Each of the content portions 153 may correspond to a distinct timesegment of the particular content item. In some cases, multiplealternative content portions 153 may be provided for time segments,e.g., both English and Spanish language audio tracks, different bitrateswith different encoding qualities, and so on. The content portions 153may include Moving Pictures Experts Group (MPEG) video data, highefficiency video coding (HEVC) data, H.264 data, Flash® media data, MPEGlayer 3 (MP3) audio data, Dolby Digital® audio data, Advanced AudioCoding (AAC) audio data, data for subtitles, etc. The content portions153 may include a high-quality version 159 a that will be used for thevideo stream 130, a low-quality version 159 b that will be used for thevideo file 121 that is predictively cached, and possibly other versions.

The manifests 155 may describe, for example, how a particular contentitem is made up of various content portions 153. The manifest 155 mayinclude identifiers for content portions 153 that make up the contentitem along with sequence-specifying data so that the client 106 canobtain and render the content portions 153 in the correct order. Themanifest 155 may also identify various alternative content portions 153for a content item such as, for example, alternative languages,alternative bitrates, and other alternatives. In some cases, themanifest 155 may provide license-related information, including thelocation of the decryption keys 157.

The decryption keys 157 may be employed by the client 106 to decryptcontent portions 153 which are encrypted under digital rights management(DRM) technologies. A decryption key 157 may be sent along with thecontent portions 153 if the client 106 has rights to the correspondingcontent item. The rights to the corresponding content item may expire ata particular time, after a time period, upon a certain number of playsfor the content item, or at some other time. Thus, the decryption keys157 may be configured to expire in response to expiration of the rightsof the client 106 to the corresponding content item. In someembodiments, the decryption keys 157 may be referred to as “licenses”for the corresponding content items.

The content availabilities 158 may indicate dates or times at which thecontent becomes available and/or unavailable. The content availabilities158 may be generally applicable or may apply to certain classes ofusers, classes of consumption (e.g., purchase or rental), or classes ofsubscriptions. Once content is made available, in some cases, thecontent may later be made unavailable. For example, content may be madeavailable for free for users having a certain membership statusbeginning with a starting date. However, the content may be dropped fromthe promotion after an expiration date. The content availabilities 158may be used to indicate new releases, expiring releases, and/or otherclasses of content, which may, in some cases, be of particular interestto users so as to result in adding content to a cache 118 when thecontent meets certain availability criteria. For example, a first usermay express a particular interest in new releases within the past month,while a second user may express a particular interest in content that isto expire from a membership program within the next week.

The promotion data 149 may indicate which content is actively beingpromoted within a content access application, a network site, or othervenue where content is promoted. Whether content is promoted may factorin whether the content is selected to be predictively cached. Forexample, content that is heavily promoted via a gateway page of anetwork site may be more likely to be selected by a user. In somescenarios, the promotions may be associated with a discount or otherincentive that may lead the user to select the content for use.

The popularity data 150 may indicate the relative popularity of contentaccording to various categorizations. For example, the popularity data150 may indicate relative popularity of content with respect to allcontent, relative popularity of content within a specific genre,relative popularity of content among certain demographics orclassifications of users, and so on. A user may be more likely to usepopular content as compared to unpopular content, thus popularity mayfactor into determining whether to predictively cache content items.

The content similarity data 152 may indicate which content is similar toother content. In one embodiment, the content similarity data 152 may begenerated by a collaborative filtering approach based upon consumptionof content by a pool of users or other data sets. Users may be morelikely to consume content that is similar to content they havepreviously consumed or in which they otherwise indicated an interest.

The user account data 148 may include various data associated with useraccounts with the content server 139. Such accounts may be explicitlyregistered and configured by users or may be created implicitly based onclient interaction with the content server 139. The user account data148 may include, for example, behavior history 160, content reviews 161,real-time behavior data 162, subscription status 163, bandwidth history164, content preferences 166, watch lists 168, recommended lists 170,subaccount data 172, content rights 175, and other data. In addition,security credentials, contact information, payment instruments, and/orother user-related data may be stored in the user account data 148.

The behavior history 160 describes historical behavior of the userassociated with the user account. Such behavior may include a contentconsumption history describing which content items the user has viewed,downloaded, rented, purchased, etc. In one example, the contentconsumption history corresponds to a media consumption historyindicating which media content items the user has viewed, downloaded,rented, purchased, etc. Such behavior may also include a browse historytracking network pages or content the user has previously accessed, asearch history tracking previous search queries, subscription history,purchase and browse history for non-content items, and/or other forms ofonline behavior. As a non-limiting example, a user who views a trailerfor a movie, as recorded in the behavior history 160, may be more likelyto view the movie soon afterward.

The real-time behavior data 162 may include data describing what theuser is currently doing, e.g., what content the user is currentlybrowsing, what search queries the user is currently executing, whatsearch results are being displayed to the user, etc. The real-timebehavior data 162 may be observed by the content server 139 or collectedfrom reports by the client 106. For example, the client 106 may beconfigured to report to the content server 139 that the user is hoveringa cursor over a description of a certain content item in a userinterface. In some embodiments, the real-time behavior data 162 may bemaintained in the client 106 rather than the computing environment 103.

The bandwidth history 164 profiles the network bandwidth available forthe user through the client 106. The bandwidth history 164 may beemployed to select from among multiple bitrates of content itemsautomatically for predictive caching. If the user employs multipleclients 106, multiple profiles may be created in the bandwidth history164. Also, multiple location-dependent profiles may be created forclients 106 that are mobile devices. As a non-limiting example, a usermay have third-generation (3G) cellular data access at an officelocation, but high-speed Wi-Fi data access at a home location, therebyresulting in multiple location-dependent bandwidth profiles for the sameclient 106 in the bandwidth history 164.

The content preferences 166 include various preferences inferred fromuser behavior or explicitly configured by users. Such preferences may berelated to media content quality (e.g., bitrate, codec, etc.), languagepreferences, subtitle preferences, closed captioning preferences,supplemental content preferences (e.g., relating to directors' oractors' commentaries, etc.), parental control preferences, and so on.The watch lists 168 may correspond to lists of content items in whichusers have explicitly indicated that they desire to consume the contentat some time in the future. The recommended lists 170 correspond tolists of content items generated for each user by the prediction engine136.

The subaccount data 172 may be employed to describe preferences orbehaviors that differ across multiple users of a user account. Forinstance, a family may have a single user account but subaccounts foreach member of the family. Each user may explicitly log in to asubaccount, or the subaccount may be inferred based on time of day, dayof the week, identity or type of the client 106, location of the client106, and/or other factors. In some cases, one user may be associatedwith multiple subaccounts. Further, a subaccount may be associated withmultiple users. The subaccount data 172 may specify restrictions oncontent access in some cases. As a non-limiting example, a subaccountfor a child may be limited to access only child-friendly content fromapproved sources. In some cases, different subaccounts may be associatedwith different clients 106.

The content rights 175 may describe the rights to content which areassociated with the user account. For example, a user may have asubscription to certain content or all content available through thecontent server 139. Such a subscription may be for indefinite use,time-limited use, device-limited use, and/or other licensingarrangements. Alternatively, a user may purchase or lease content on aper-content-item basis. The subscription status 163 may indicate thatstatus of the user with respect to content subscriptions, programmemberships, promotions, and/or other statuses that may entitle the userto access certain content or access certain content for no additionalcharge or an otherwise reduced fee.

The content reviews 161 may correspond to user-created ratings and/orreviews of content. For example, the content preferences 166 of a usermay be inferred based upon the types of content that he or she writesfavorable or unfavorable reviews upon. When a user rates content from acertain genre negatively, he or she may be considered less likely toselect content from that genre in the future. However, in some cases,when a user frequently writes reviews or enters ratings for a certaingenre, it may be inferred that the user is likely to select content fromthat genre, regardless of whether the user liked or disliked thecontent.

The client 106 is representative of a plurality of client devices thatmay be coupled to the network 109. The client 106 may comprise, forexample, a processor-based system such as a computer system. Such acomputer system may be embodied in the form of desktop computers, laptopcomputers, personal digital assistants, cellular telephones,smartphones, set-top boxes, music players, web pads, tablet computersystems, game consoles, electronic book readers, or other devices withlike capability. The client 106 may include a display 177. The display177 may comprise, for example, one or more devices such as liquidcrystal display (LCD) displays, electrophoretic ink (E ink) displays,gas plasma-based flat panel displays, organic light emitting diode(OLED) displays, LCD projectors, or other types of display devices, etc.

The client 106 may be configured to execute various applications such asa content access application 179, a caching system 180, and/or otherapplications. The content access application 179 may be executed in theclient 106, for example, to access and render content items from thecomputing environment 103 and/or other servers. Moreover, the contentaccess application 179 may access various other network content servedup by the computing environment 103 and/or other servers, therebyrendering a user interface 112 on the display 177. The content accessapplication 179 may function as a video player application and mayprovide various video player functionality including, for example,initiating playback, stopping playback, pausing playback, adjustingvolume, setting preferences, browsing for media content, searching formedia content, recommending media content by rendering recommendations,and so on. In one embodiment, the content access application 179comprises a browser application.

The caching system 180 is executed to predict various content items thatthe user is likely to access and to cache video files 121 (FIG. 1A) inthe cache 118 to facilitate instantaneous use. The cache 118 may bemaintained using a plurality of cache segments. In one embodiment, thecache 118 is structured to have a reactive segment 181, a previouslyaccessed segment 182, a predictive segment 183, and/or other cachesegments. The cache segments may utilize different content selectioncriteria, as discussed below. The different cache segments may alsoutilize different cache eviction/purging criteria. In some scenarios,cache segments may be tied to particular storage devices. For example,one cache segment may be on one storage device, while another cachesegment may be on another storage device. In one embodiment, the cachingsystem 180 receives caching instructions from the computing environment103 and is configured to carry out the caching instructions. In variousembodiments, the prediction engine 136 or portions thereof may beimplemented client-side within the caching system 180.

The reactive segment 181 may include content that is immediatelyselectable for use or playback via a current user interface 112 renderedby the content access application 179. For example, the current userinterface 112 may have buttons, drop-down boxes, links, and/or otheruser interface components that, when selected, initiate usage orplayback of a particular content item. In some cases, content may beselected for the reactive segment 181 when selectable via apredetermined number of actions by way of the current user interface112. For example, the reactive segment 181 may include all content thatis selectable via the current user interface 112 and any user interface112 directly reachable via the current user interface 112. It isunderstood that different user interface 112 screens and portionsthereof may be associated with different reactive caching policies. Forexample, the proportion of titles reactively cached on a search page maydiffer from the proportion of titles reactively cached on a programseason detail page. A feedback loop may be employed to improve the hitrate of titles cached in the reactive segment 181 over time with respectto the behavior of users.

The previously accessed segment 182 may include content that the userhas previously used. For example, where the content is a video, the usermay have watched the video in its entirety or may have paused or stoppedthe video at some point before the end. Where the user has paused orstopped the video, the user may likely return at some later time toresume the video. Similarly, even if the user has watched the video inits entirety, the user may return later and review it. Such behavior maybe user dependent; i.e., some users may be more likely to review orresume content, while others may more likely abandon content. In onescenario, where the user has paused or stopped the content at a positionother than at the beginning, the previously accessed segment 182 mayinclude a portion of the video file 121 that commences with the positionwhere the content has been paused or stopped.

The predictive segment 183 may include content that the user ispredicted to access based upon a variety of data sources. For example,the caching system 180 may prefetch content corresponding to thatspecified in the prediction data 142. The predictive segment 183 may befilled based upon resource availability and priority of the contentspecified in the prediction data 142. As non-limiting examples, thecontent in the predictive segment 183 may be selected based at least inpart on user account data 148 associated with the user, promotion data149, popularity data 150, content availabilities 158, content similaritydata 152, and/or other data.

In various scenarios, the cache segments of the cache 118 may have fixedor dynamic relative maximum sizes. The sizes may be established based atleast in part on the number of content items (e.g., titles), disk spaceconsumed for the respective content items, user preferences, userbehavior (e.g., for some users a larger reactive cache may be preferred,and so on), and/or other factors. In one scenario, the predictivesegment 183 may be larger than the previously accessed segment 182,which may in turn be larger than the reactive segment 181. However, dueto update frequencies, the contents of the reactive segment 181 may beupdated more frequently than, for example, the predictive segment 183.

The content access application 179 may include various decodingcomponents 184 and decryption components 185 corresponding to logic thatfacilitates usage or playback of content items. The caching system 180may also initialize various decoding components 184, decryptioncomponents 185, etc. for content items in the cache 118. In this regard,various objects may be instantiated in the memory of the client 106 forthe decoding components 184 and the decryption components 185. Theoverall size of the cache 118 may depend, for example, onuser-configured parameters, the available data storage in the client106, the bandwidth available to the client 106 over the network 109, oron other factors. In various embodiments, the client 106 may beconfigured to make predictive caching decisions and/or the computingenvironment 103 may be configured to make predictive caching decisions.

The client 106 may also include a secure data store 187 for storage ofdecryption keys 157 used in decrypting content items to which the userhas rights in the client 106. The secure data store 187 may comply withvarious rules regarding security for storage of DRM licenses. The securedata store 187 may have relatively limited storage space for decryptionkeys 157. In some cases, the limited storage space in the secure datastore 187 may in turn limit the size of the cache 118. The cachingsystem 180 may be configured to install the decryption keys 157 in thesecure data store 187 which the corresponding content items arepredictively cached. The client 106 may be configured to executeapplications beyond the content access application 179 and the cachingsystem 180 such as, for example, browsers, mobile applications, emailapplications, social networking applications, and/or other applications.

Next, a general description of the operation of the various componentsof the networked environment 100 a is provided. To begin, users mayregister and interact with the content server 139 such that behaviorhistory 160 (e.g., consumption history, etc.), bandwidth history 164,content preferences 166, watch lists 168, and/or other data in the useraccount data 148 is created for a content access account.

As users interact with the content server 139, the popularity data 150and the content similarity data 152 may be generated. In some cases, thepopularity data 150 and the content similarity data 152 may be obtainedfrom other sources. Users may add content to their watch lists 168 andwrite reviews for the content reviews 161. Administrators may configurevarious promotions in the promotion data 149.

The recommended lists 170 and/or other data indicating content that theuser is likely to select may be sent to the client 106 as predictiondata 142. From a list of recommended content items, the caching system180 may select a subset of the list based at least in part on arespective priority of the content items, an available data storage forthe client 106, available storage in the secure data store 187,available bandwidth, power state in the client 106, costs associatedwith the network 109 connection to the client 106, type of network 109connection to the client 106, configuration parameters, and/or otherfactors. In addition, the caching system 180 may determine content itemsto be cached in the reactive segment 181, the previously accessedsegment 182, and/or other cache segments. In one embodiment, the cachingsystem 180 determines the selected subset according to a directive fromthe computing environment 103.

As non-limiting examples, a content item may be selected for cachingbased at least in part on a subscription status 163 of the user andwhether a discounted price for the content item is available for theuser given the subscription status 163, whether the content item willbecome unavailable to the user within a predetermined time periodaccording to the content rights 175 and the content availabilities 158,whether the content item is recommended to the user via a user interface112 of a content access application 179, and/or other factors.

The caching system 180 proceeds to predictively cache the content itemsin the selected subset. In doing so, the caching system 180 may obtainthe video files 121 via the content portions 153 corresponding to thelow-quality version 159 b before the user selects any of thecorresponding video content features for playback. To this end, thecaching system 180 may obtain the low-quality version 159 b contentportions 153 and metadata such as manifests 155 and decryption keys 157from the content server 139.

The content portions 153 may be sent in an encrypted format. To handlethis, the caching system 180 may obtain decryption keys 157, which arethen installed in the secure data store 187 to handle the decryption.The caching system 180 may spin up and initialize hardware and/orsoftware resources of the client 106, to include, for example, decodingcomponents 184, decryption components 185, and other components of thecontent access application 179. Hardware resources such as displays 117may be configured. Thus, the caching system 180 may perform someprocessing relative to the metadata and/or the initial portion of thecontent item in order to prepare the client 106 for playback of thepredictively cached content items prior to the user explicitlyindicating that use or playback is desired.

Seamless failover playback may then be provided by the content accessapplication 179 when any of the selected subset of content items isselected for use or playback by the user. The content access application179 is configured to stream a selected video content featurecorresponding to high-quality version 159 a content portions 153 fromthe content server 139 as a video stream 130. Although described as aseamless failover, it is understood that such playback may include afade transition or other transition.

It is understood that the systems of the client 106 described herein maybe employed with a second screen experience. For example, multipledisplays 177 may be utilized, with one display 177 rendering a controluser interface 112 for the content access application 179 and anotherdisplay 177 rendering the actual content. The displays 177 maycorrespond to the same client 106 or multiple clients 106 that are indata communication.

Moving on to FIG. 1C, shown is a drawing presenting a view of anetworked environment 100 b that facilitates local cached file exchange.The networked environment 100 b includes the computing environment 103,a client 106 a, and a client 106 b in data communication via the network109. Although two clients 106 are shown, it is understood that the twoclients 106 are representative of any plurality of clients 106.Additionally, the clients 106 a and 106 b may be in data communicationvia a local network 190. The local network 190 may comprise an Ethernetnetwork, a Wi-Fi® network, a Multimedia over Coax Alliance (MoCA)network, a Bluetooth® network, a Home Phoneline Networking Alliance(HomePNA®) network, and/or other networks that offer relativelyunconstrained bandwidth between local devices.

In the networked environment 100 b, the client 106 a is able to obtaincached data 192 from the client 106 b directly via the local network 190without having to go through the potentially congested network 109 toobtain the data from the computing environment 103. That is to say, thecaching system 180 (FIG. 1B) on the client 106 a is able to obtain thecached data 192 from a cache 118 (FIG. 1B) maintained by the client 106b. In this regard, the client 106 a is able to determine that the cacheddata 192 that is needed is stored by the client 106 b either bycommunicating directly with the client 106 b or by communicating withthe computing environment 103. Discovery-type broadcast messaging may besent across the local network 190 so that each client 106 is aware ofthe state of the other caches 118 existing in clients 106 upon the localnetwork 190. The cached data 192 may comprise video files 121 (FIG. 1A)and/or other data.

Referring next to FIG. 2, shown is a flowchart that provides one exampleof the operation of a portion of the caching system 180 according tovarious embodiments. It is understood that the flowchart of FIG. 2provides merely an example of the many different types of functionalarrangements that may be employed to implement the operation of theportion of the caching system 180 as described herein. As analternative, the flowchart of FIG. 2 may be viewed as depicting anexample method implemented in the client 106 (FIGS. 1A & 1B) accordingto one or more embodiments.

Beginning with box 203, the caching system 180 may obtain predictiondata 142 (FIG. 1B) from the computing environment 103 (FIG. 1B). Theprediction data 142 may indicate a list of content items that the useris at the client 106 is predicted to access. Such prediction data 142may be generated based at least in part on, for example, behaviorhistory 160 (FIG. 1B) including content consumption history, contentpreferences 166 (FIG. 1B), real-time behavior data 162 (FIG. 1B), and/orother data. The list of recommended content items may have a priorityassociated with each content item in the list. Such a priority mayindicate a relative likelihood that the user will want to consume theparticular content item.

In box 206, the caching system 180 determines content items forpredictive caching. Indications of the content items may be added to aqueue for caching in association with respective priorities.Subsequently, the indications of the content items may be selected fromthe queue for caching to be implemented. The selection may be driven bypriority of the respective content items, available resources in theclient 106 (e.g., available memory or data storage allocated for thecache 118 (FIGS. 1A & 1B)), available storage in the secure data store187 (FIG. 1B), available bandwidth on the network 109 (FIGS. 1A & 1B)for the client 106, bandwidth history 164 (FIG. 1B), content preferences166 (FIG. 1B), real-time behavior data 162 available to the client 106,configuration parameters, and/or other factors. Where the cache 118 issegmented, the different selection criteria for the segments and therespective capacities of the segments may be considered.

In box 209, the caching system 180 determines whether previously cachedcontent from the cache 118 is to be purged. Such content may be purgedin order to free up resources for other content that is determined to bemore likely to be consumed by the user. The previously cached contentmay also be rendered obsolete by a change to the factors which promptedits initial selection to be predictively cached, e.g., if the content isno longer timely, if the real-time behavior of the user that promptedthe predictive caching of the content has changed, if the user hascompleted consuming the content, and so on. In some cases, the user mayexplicitly request that content be purged from the cache 118. In somecases, the caching system 180 may be able to resize a target cachesegment to accommodate the content item selected for predictive caching.

If previously cached content is to be purged, the caching system 180moves from box 209 to box 212 and determines which of the previouslycached content items are to be purged. In some cases, the user mayexplicitly identify which content is to be purged. In box 215, thecaching system 180 deallocates resources in the client 106 that had beenallocated to the content items that are to be purged. In doing so, thecaching system 180 may, for example, remove video files 121 (FIG. 1A)from the cache 118, remove unnecessary decryption keys 157 (FIG. 1B)from the secure data store 187, terminate unnecessary decodingcomponents 184 (FIG. 1B) or decryption components 185 (FIG. 1B), and soon. The caching system 180 then proceeds to box 216. If the cachingsystem 180 instead decides not to purge previously cached content, thecaching system 180 moves from box 209 to box 216.

In box 216, the caching system 180 determines the location of thecontent to be cached. In some instances, the video files 121 and/orother data for the content to be cached may be cached by another client106 upon the local network 190 (FIG. 1C). In other instances, thecaching system 180 may have to retrieve the data from the computingenvironment 103. Existing cached content accessible via the localnetwork 190 may be preferred to minimize data usage for the network 109and/or to improve caching performance.

In box 218, the caching system 180 obtains content portions 153 (FIG.1B) corresponding to a low-quality version 159 b (FIG. 1A) from thecontent server 139 (FIG. 1B) for the video files 121 that are to bepredictively cached. The initial portions may correspond to thebeginning of the content item, a location where the user left off inconsuming the content item, a popular location within the content item,and/or other starting portions within the content item. The cachingsystem 180 may also obtain manifests 155 (FIG. 1B), decryption keys 157,and/or other metadata. In box 224, the caching system 180 may initializevarious components in the client 106 to facilitate playback of thepredictively cached video files 121. This may include, for example,launching and/or initializing decoding components 184 and/or decryptioncomponents 185, storing decryption keys 157 in the secure data store187, and/or performing other tasks. In box 230, the caching system 180may report caching metrics 143 (FIG. 1B) to the computing environment103. Thereafter, the portion of the caching system 180 ends.

Turning now to FIG. 3, shown is a flowchart that provides one example ofthe operation of a portion of the content access application 179according to various embodiments. It is understood that the flowchart ofFIG. 3 provides merely an example of the many different types offunctional arrangements that may be employed to implement the operationof the portion of the content access application 179 as describedherein. As an alternative, the flowchart of FIG. 3 may be viewed asdepicting an example method implemented in the client 106 (FIGS. 1A &1B) according to one or more embodiments.

Beginning with box 303, the content access application 179 obtains auser directive to play a video content feature. For instance, a user maynavigate to a user interface 112 (FIGS. 1A & 1B) that presents a contentitem, and the user may select a “play” button or other similar userinterface component. In box 306, the content access application 179determines whether the video file 121 (FIG. 1A) corresponding to thelow-quality version 159 b (FIG. 1A) has been predictively cached in theclient 106. If the content item has not been predictively cached in theclient 106, or if the predictive caching is incomplete, the contentaccess application 179 may continue to box 309.

In box 309, the content access application 179 may obtain thelow-quality video file 121 from the content server 139 (FIG. 1B).Alternatively, if available, the content access application 179 mayobtain the video file 121 from another client 106 coupled to a localnetwork 190 (FIG. 1C). In addition to obtaining the video file 121,manifests 155 (FIG. 1B), decryption keys 157 (FIG. 1B), and/or othermetadata may be obtained and various components in the client 106 may beinitialized. This may include, for example, launching and/orinitializing decoding components 184 (FIG. 1B) and/or decryptioncomponents 185 (FIG. 1B), storing decryption keys 157 (FIG. 1B) in thesecure data store 187, and/or performing other tasks. The content accessapplication 179 then continues to box 312. If the video file 121 hasbeen predictively cached, the content access application 179 transitionsfrom box 306 to box 312.

In box 312, the content access application 179 may determine the networkconnection status for the client 106. For example, the client 106 may beentirely disconnected from the network 109 (FIG. 1B), connected to acellular network, connected to a wireless local area network, or havesome other connection arrangement. The content access application 179may probe the connection to determine available bandwidth to the contentserver 139. The content access application 179 may also determine a typeof device, e.g., a type of mobile device, to which the client 106corresponds, and/or a cost associated with data transfer to the client106.

In box 315, the content access application 179 determines whether toobtain the video stream 130 (FIG. 1B) from the content server 139,corresponding to a high-quality version 159 a (FIG. 1B) of the videocontent feature. Such a determination may be based at least in part onthe network connection status, including the available cost, type ofnetwork connection, bandwidth, and/or other factors. In some cases, auser may enable an offline mode setting to force the content accessapplication 179 to use cached data. If the content access application179 is not to obtain the video stream 130 at this time, the contentaccess application 179 proceeds to box 318 and commences rendering ofthe cached low-quality video file 121 for playback on the display 177(FIG. 1B). The content access application 179 then returns to box 312and again determines the network connection status for the client 106.

If the content access application 179 instead determines that the videostream 130 is to be obtained, the content access application 179progresses from box 315 to box 321. In box 321, the content accessapplication 179 obtains the high-quality video stream 130 from thecontent server 139 over the network 109. In box 324, the content accessapplication 179 renders the video stream 130 for playback on the display177. In box 327, the content access application 179 determines whetherplayback of the video content feature has finished. If playback hasfinished, the operation of the portion of the content access application179 ends. Otherwise, the content access application 179 continues to box330 and determines whether playback of the video content feature hasbeen interrupted. For example, the content access application 179 mayassess the network connection status as in box 312, determine that thevideo stream 130 is not available, or that the availability of the videostream 130 is associated with an unacceptable cost. If no interruptionoccurs, the content access application 179 returns to box 321 andcontinues obtaining and rendering the high-quality video stream 130.

If an interruption occurs, the content access application 179 moves tobox 333 and renders the cached low-quality video file 121 for playbackon the display 177. If the playback of the video stream 130 left off ata particular time in the video content feature, the playback of thelow-quality video file 121 may automatically commence at the particulartime in the video content feature, thereby providing a seamless playbackexperience. In box 334, the content access application 179 determineswhether playback of the video content feature has finished. If playbackhas finished, the operation of the portion of the content accessapplication 179 ends. Otherwise, in box 336, the content accessapplication 179 determines whether the high-quality video stream 130 hasagain become available. For example, the content access application 179may assess the network connection status as in box 312, determine thatthe video stream 130 is again available, or determine that theavailability of the video stream 130 is associated with an acceptablecost.

If the video stream 130 is not available, the content access application179 returns to box 333 and continues rendering the video file 121 forplayback on the display 177. If the video stream 130 is again available,the content access application 179 returns to box 321 and obtains andrenders the video stream 130. The playback of the video stream 130 maycommence at a later time in the video content feature, where theplayback of the video file 121 ends at the later time, again providingfor a seamless transition from cached to streamed sources.

Moving on to FIG. 4, shown is a flowchart that provides one example ofthe operation of a portion of the content server 139 (FIGS. 1A & 1B)according to various embodiments. It is understood that the flowchart ofFIG. 4 provides merely an example of the many different types offunctional arrangements that may be employed to implement the operationof the portion of the content server 139 as described herein. As analternative, the flowchart of FIG. 4 may be viewed as depicting anexample method implemented in the computing environment 103 (FIGS. 1A &1B) according to one or more embodiments.

Beginning with box 403, the content server 139 authenticates a user at aclient 106 (FIGS. 1A & 1B). In some cases, the user may be associatedwith a subaccount. The authentication may be performed by a cookie, by ausername/password combination, and/or by another security credential. Inbox 406, the content server 139 provides prediction data 142 (FIG. 1B)to the client 106. In some cases, the content server 139 may providedirectives to the client 106 to predictively cache low-quality versions159 b (FIG. 1B) of certain content items. In box 409, the content server139 obtains a request for content data 145 (FIG. 1B) from the client106. The request may be for content portions 153 (FIG. 1B), manifests155 (FIG. 1B), decryption keys 157 (FIG. 1B), and/or other content data145.

In box 412, the content server 139 determines whether the client 106 hasrights to the content item to which the content data 145 pertains. Ifnot, the content server 139 may prompt the user to acquire the rights inbox 415. For example, the content server 139 may send data encoding auser interface 112 (FIGS. 1A & 1B) to the client 106, where the userinterface 112 prompts the user to purchase the content item or asubscription. Thereafter, the portion of the content server 139 ends. Insome cases, the encrypted content portions 153 and manifests 155 may besent to the client 106 without the decryption key 157 if the client 106does not have the rights.

If the client 106 does have the rights, the content server 139 movesfrom box 412 to box 418 and sends the content data 145 to the client 106over the network 109 (FIGS. 1A & 1B). In some cases, the content server139 may select from multiple bitrates for the content portions 153,multiple languages in the content portions 153, and/or otheralternatives based on data such as bandwidth history 164 (FIG. 1B),content preferences 166 (FIG. 1B), etc. The bitrate may be adaptivebased at least in part on the currently available bandwidth for theclient 106. In box 421, the content server 139 updates the behaviorhistory 160 (FIG. 1B), the bandwidth history 164 (FIG. 1B), and/or otherdata. In box 424, the content server 139 may obtain caching metrics 143(FIG. 1B) from the client 106. The content server 139 may then recordthe caching metrics 143, which may then be used to improve the operationof the caching system 180 (FIG. 1B) and/or the prediction engine 136(FIG. 1B). Thereafter, the portion of the content server 139 ends.

With reference to FIG. 5, shown is a schematic block diagram of thecomputing environment 103 according to an embodiment of the presentdisclosure. The computing environment 103 includes one or more computingdevices 500. Each computing device 500 includes at least one processorcircuit, for example, having a processor 503 and a memory 506, both ofwhich are coupled to a local interface 509. To this end, each computingdevice 500 may comprise, for example, at least one server computer orlike device. The local interface 509 may comprise, for example, a databus with an accompanying address/control bus or other bus structure ascan be appreciated.

Stored in the memory 506 are both data and several components that areexecutable by the processor 503. In particular, stored in the memory 506and executable by the processor 503 are the prediction engine 136, thecontent server 139, and potentially other applications. Also stored inthe memory 506 may be a data store 133 and other data. In addition, anoperating system may be stored in the memory 506 and executable by theprocessor 503. The client 106 (FIGS. 1A & 1B) may correspond to asimilar computing device 500 having a processor 503 and memory 506.

It is understood that there may be other applications that are stored inthe memory 506 and are executable by the processor 503 as can beappreciated. Where any component discussed herein is implemented in theform of software, any one of a number of programming languages may beemployed such as, for example, C, C++, C#, Objective C, Java®,JavaScript®, Perl, PHP, Visual Basic®, Python®, Ruby, Flash®, or otherprogramming languages.

A number of software components are stored in the memory 506 and areexecutable by the processor 503. In this respect, the term “executable”means a program file that is in a form that can ultimately be run by theprocessor 503. Examples of executable programs may be, for example, acompiled program that can be translated into machine code in a formatthat can be loaded into a random access portion of the memory 506 andrun by the processor 503, source code that may be expressed in properformat such as object code that is capable of being loaded into a randomaccess portion of the memory 506 and executed by the processor 503, orsource code that may be interpreted by another executable program togenerate instructions in a random access portion of the memory 506 to beexecuted by the processor 503, etc. An executable program may be storedin any portion or component of the memory 506 including, for example,random access memory (RAM), read-only memory (ROM), hard drive,solid-state drive, USB flash drive, memory card, optical disc such ascompact disc (CD) or digital versatile disc (DVD), floppy disk, magnetictape, or other memory components.

The memory 506 is defined herein as including both volatile andnonvolatile memory and data storage components. Volatile components arethose that do not retain data values upon loss of power. Nonvolatilecomponents are those that retain data upon a loss of power. Thus, thememory 506 may comprise, for example, random access memory (RAM),read-only memory (ROM), hard disk drives, solid-state drives, USB flashdrives, memory cards accessed via a memory card reader, floppy disksaccessed via an associated floppy disk drive, optical discs accessed viaan optical disc drive, magnetic tapes accessed via an appropriate tapedrive, and/or other memory components, or a combination of any two ormore of these memory components. In addition, the RAM may comprise, forexample, static random access memory (SRAM), dynamic random accessmemory (DRAM), or magnetic random access memory (MRAM) and other suchdevices. The ROM may comprise, for example, a programmable read-onlymemory (PROM), an erasable programmable read-only memory (EPROM), anelectrically erasable programmable read-only memory (EEPROM), or otherlike memory device.

Also, the processor 503 may represent multiple processors 503 and/ormultiple processor cores and the memory 506 may represent multiplememories 506 that operate in parallel processing circuits, respectively.In such a case, the local interface 509 may be an appropriate networkthat facilitates communication between any two of the multipleprocessors 503, between any processor 503 and any of the memories 506,or between any two of the memories 506, etc. The local interface 509 maycomprise additional systems designed to coordinate this communication,including, for example, performing load balancing. The processor 503 maybe of electrical or of some other available construction.

Although the prediction engine 136, the content server 139, the contentaccess application 179 (FIG. 1B), the caching system 180 (FIG. 1B), andother various systems described herein may be embodied in software orcode executed by general purpose hardware as discussed above, as analternative the same may also be embodied in dedicated hardware or acombination of software/general purpose hardware and dedicated hardware.If embodied in dedicated hardware, each can be implemented as a circuitor state machine that employs any one of or a combination of a number oftechnologies. These technologies may include, but are not limited to,discrete logic circuits having logic gates for implementing variouslogic functions upon an application of one or more data signals,application specific integrated circuits (ASICs) having appropriatelogic gates, field-programmable gate arrays (FPGAs), or othercomponents, etc. Such technologies are generally well known by thoseskilled in the art and, consequently, are not described in detailherein.

The flowcharts of FIGS. 2-4 show the functionality and operation of animplementation of portions of the caching system 180, the content accessapplication 179, and the content server 139. If embodied in software,each block may represent a module, segment, or portion of code thatcomprises program instructions to implement the specified logicalfunction(s). The program instructions may be embodied in the form ofsource code that comprises human-readable statements written in aprogramming language or machine code that comprises numericalinstructions recognizable by a suitable execution system such as aprocessor 503 in a computer system or other system. The machine code maybe converted from the source code, etc. If embodied in hardware, eachblock may represent a circuit or a number of interconnected circuits toimplement the specified logical function(s).

Although the flowcharts of FIGS. 2-4 show a specific order of execution,it is understood that the order of execution may differ from that whichis depicted. For example, the order of execution of two or more blocksmay be scrambled relative to the order shown. Also, two or more blocksshown in succession in FIGS. 2-4 may be executed concurrently or withpartial concurrence. Further, in some embodiments, one or more of theblocks shown in FIGS. 2-4 may be skipped or omitted. In addition, anynumber of counters, state variables, warning semaphores, or messagesmight be added to the logical flow described herein, for purposes ofenhanced utility, accounting, performance measurement, or providingtroubleshooting aids, etc. It is understood that all such variations arewithin the scope of the present disclosure.

Also, any logic or application described herein, including theprediction engine 136, the content server 139, the content accessapplication 179, and the caching system 180, that comprises software orcode can be embodied in any non-transitory computer-readable medium foruse by or in connection with an instruction execution system such as,for example, a processor 503 in a computer system or other system. Inthis sense, the logic may comprise, for example, statements includinginstructions and declarations that can be fetched from thecomputer-readable medium and executed by the instruction executionsystem. In the context of the present disclosure, a “computer-readablemedium” can be any medium that can contain, store, or maintain the logicor application described herein for use by or in connection with theinstruction execution system.

The computer-readable medium can comprise any one of many physical mediasuch as, for example, magnetic, optical, or semiconductor media. Morespecific examples of a suitable computer-readable medium would include,but are not limited to, magnetic tapes, magnetic floppy diskettes,magnetic hard drives, memory cards, solid-state drives, USB flashdrives, or optical discs. Also, the computer-readable medium may be arandom access memory (RAM) including, for example, static random accessmemory (SRAM) and dynamic random access memory (DRAM), or magneticrandom access memory (MRAM). In addition, the computer-readable mediummay be a read-only memory (ROM), a programmable read-only memory (PROM),an erasable programmable read-only memory (EPROM), an electricallyerasable programmable read-only memory (EEPROM), or other type of memorydevice.

Further, any logic or application described herein, including theprediction engine 136, the content server 139, the content accessapplication 179, and the caching system 180, may be implemented andstructured in a variety of ways. For example, one or more applicationsdescribed may be implemented as modules or components of a singleapplication. Further, one or more applications described herein may beexecuted in shared or separate computing devices or a combinationthereof. For example, a plurality of the applications described hereinmay execute in the same computing device 500, or in multiple computingdevices in the same computing environment 103. Additionally, it isunderstood that terms such as “application,” “service,” “system,”“engine,” “module,” and so on may be interchangeable and are notintended to be limiting.

Disjunctive language such as the phrase “at least one of X, Y, or Z,”unless specifically stated otherwise, is otherwise understood with thecontext as used in general to present that an item, term, etc., may beeither X, Y, or Z, or any combination thereof (e.g., X, Y, and/or Z).Thus, such disjunctive language is not generally intended to, and shouldnot, imply that certain embodiments require at least one of X, at leastone of Y, or at least one of Z to each be present.

It should be emphasized that the above-described embodiments of thepresent disclosure are merely possible examples of implementations setforth for a clear understanding of the principles of the disclosure.Many variations and modifications may be made to the above-describedembodiment(s) without departing substantially from the spirit andprinciples of the disclosure. All such modifications and variations areintended to be included herein within the scope of this disclosure andprotected by the following claims.

The invention claimed is:
 1. A non-transitory computer-readable mediumembodying at least one program executable in at least one computingdevice, wherein when executed the at least one program causes the atleast one computing device to at least: determine a plurality of videofiles to be predictively cached based at least in part on a viewinghistory of a user, the plurality of video files corresponding to aplurality of video content features; obtain the plurality of video filesbefore the user expresses an interest in playing any of the plurality ofvideo content features; obtain a directive from the user to play aparticular video content feature of the plurality of video contentfeatures; in response to the directive, obtain a video streamcorresponding to the particular video content feature, the video streamhaving a higher bitrate than one of the plurality of video files thatcorresponds to the particular video content feature; render the videostream upon a display; detect an interruption in the video stream at aparticular time in the particular video content feature; render the oneof the plurality of video files upon the display in place of the videostream beginning at the particular time in response to detecting theinterruption; and resume rendering of the video stream in place of theone of the plurality of video files at a later time in the particularvideo content feature when the video stream becomes available.
 2. Thenon-transitory computer-readable medium of claim 1, wherein theinterruption corresponds to a loss of network connectivity.
 3. A system,comprising: a computing device; and a video player applicationexecutable in the computing device, wherein when executed the videoplayer application causes the computing device to at least: determine aplurality of video files to be predictively cached based at least inpart on a viewing history of a user, the plurality of video filescorresponding to a plurality of video content features; obtain theplurality of video files before the user expresses an interest inplaying any of the plurality of video content features; obtain adirective from the user to play a particular video content feature ofthe plurality of video content features; in response to the directive,obtain a video stream corresponding to the particular video contentfeature, the video stream having a higher bitrate than one of theplurality of video files that corresponds to the particular videocontent feature; render the video stream upon a display; detect aninterruption in the video stream at a particular time in the particularvideo content feature; render the one of the plurality of video filesupon the display in place of the video stream beginning at theparticular time in response to detecting the interruption; and resumerendering of the video stream in place of the one of the plurality ofvideo files at a later time in the particular video content feature whenthe video stream becomes available.
 4. The system of claim 3, whereinwhen executed the video player application further causes the computingdevice to at least monitor a network connectivity status of thecomputing device, wherein the interruption in the video stream isdetected based at least in part on the network connectivity status. 5.The system of claim 3, wherein when executed the video playerapplication further causes the computing device to at least, in responseto detecting that the user of the computing device has enabled anoffline mode, render the one of the plurality of video files forplayback on the display in place of the video stream.
 6. The system ofclaim 3, wherein when executed the video player application furthercauses the computing device to at least, in response to detecting thatthe computing device has switched from a first type of networkconnectivity to a second type of network connectivity, render the one ofthe plurality of video files for playback on the display in place of thevideo stream.
 7. The system of claim 6, wherein the first type ofnetwork connectivity corresponds to a wireless local area networkconnection, and the second type of network connectivity corresponds to acellular network connection.
 8. The system of claim 6, wherein whenexecuted the video player application further causes the computingdevice to at least, in response to detecting that the computing devicehas switched from the second type of network connectivity to the firsttype of network connectivity, render the video stream for playback onthe display in place of the one of the plurality of video files.
 9. Thesystem of claim 3, wherein when executed the video player applicationfurther causes the computing device to at least: determine whether thecomputing device is a type of mobile device; and wherein the pluralityof video files are obtained in response to determining that thecomputing device is the type of mobile device.
 10. The system of claim3, wherein the one of the plurality of video files is encoded using afirst bitrate that is at least an order of magnitude less than a secondbitrate at which the video stream is encoded.
 11. A method, comprising:determining, by at least one computing device, a plurality of videofiles to be predictively cached based at least in part on a viewinghistory of a user, the plurality of video files corresponding to aplurality of video content features; obtaining, by the at least onecomputing device, the plurality of video files before the user expressesan interest in playing any of the plurality of video content features;obtaining, by the at least one computing device, a directive from theuser to play a particular video content feature of the plurality ofvideo content features; in response to the directive, obtaining, by theat least one computing device, a video stream corresponding to theparticular video content feature, the video stream having a higherbitrate than one of the plurality of video files that corresponds to theparticular video content feature; rendering, by the at least onecomputing device, the video stream upon a display; detecting, by the atleast one computing device, an interruption in the video stream at aparticular time in the particular video content feature; rendering, bythe at least one computing device, the one of the plurality of videofiles upon the display in place of the video stream beginning at theparticular time in response to detecting the interruption; and resuming,by the at least one computing device, rendering of the video stream inplace of the one of the plurality of video files at a later time in theparticular video content feature when the video stream becomesavailable.
 12. The method of claim 11, further comprising determining,by the at least one computing device, when to obtain the plurality ofvideo files based at least in part on a cost to obtain the plurality ofvideo files via a network.
 13. The method of claim 11, furthercomprising determining, by the at least one computing device, whether toobtain the plurality of video files based at least in part on a measureof available data storage in a data store accessible to the at least onecomputing device.
 14. The method of claim 11, further comprisingrendering, by the at least one computing device, the one of theplurality of video files instead of the video stream when obtaining thevideo stream via a network is associated with a cost.
 15. The method ofclaim 11, further comprising determining, by the at least one computingdevice, a network connectivity status, wherein the interruption in thevideo stream is detected based at least in part on the networkconnectivity status.
 16. The method of claim 11, further comprisingrendering, by the at least one computing device, the one of theplurality of video files for playback on the display in place of thevideo stream in response to detecting that an offline mode has beenenabled.
 17. The method of claim 11, further comprising rendering, bythe at least one computing device, the one of the plurality of videofiles for playback on the display in place of the video stream inresponse to detecting that a network connectivity has switched from afirst type of network connectivity to a second type of networkconnectivity.
 18. The method of claim 17, wherein the first type ofnetwork connectivity corresponds to a wireless local area networkconnection, and the second type of network connectivity corresponds to acellular network connection.
 19. The method of claim 17, furthercomprising rendering, by the at least one computing device, the videostream for playback on the display in place of the one of the pluralityof video files in response to detecting that the computing device hasswitched from the second type of network connectivity to the first typeof network connectivity.
 20. The method of claim 11, wherein the one ofthe plurality of video files is encoded using a first bitrate that is atleast an order of magnitude less than a second bitrate at which thevideo stream is encoded.